A data mining task refers to the implementation of a model for analyzing data. It includes tasks such as clustering, association rules, correlation analysis, classification, regression, and categorization, which generate descriptive or predictive models. AI generated definition based on: Expert Systems with Applications, 2014

Jan 1, 2021 · This chapter illustrates the intelligent data mining methods considering association rule mining (ARM) and the Apriori algorithm to mine information from the dataset. In addition, the data mining functionalities are employed to specify …

Sep 1, 2024 · Heterogeneous network-based methods are powerful analytical tools for many real-world data mining tasks in biomedical field. The specific aim of this survey is to examine the representative algorithms used in heterogeneous network data mining tasks and concentrate on biomedical domain to analyze the application of these techniques in the real ...

Oct 1, 2012 · Abstract Data Mining projects are implemented by following the knowledge discovery process. This process is highly complex and iterative in nature and comprises of several phases, starting off with business understanding, and followed by data understanding, data preparation, modeling, evaluation and deployment or implementation. Each phase comprises of several tasks. Knowledge Discovery and ...

Jan 1, 2018 · Abstract This paper is devoted to the main tasks in the analysis of large amounts of information and comparison of methods for their solution. The analysis of large volumes of information and identification of valuable knowledge provided by Data Mining tools. The concept of Data Mining is translated as data mining, data analysis, data collection. Due to of the huge variety of data types and ...

Jun 1, 2020 · Hybrid algorithms consisting of two different optimization techniques can be considered for future study for data mining tasks. Also, a comparative study between the suggested algorithms for data mining classification can be performed for other commercial, social, and or industrial fields.

Jan 1, 2020 · Data mining tasks are generally divided into two broad categories: descriptive and predictive (Rokach and Maimon, 2015; Tan et al., 2006). Descriptive data mining tasks are often exploratory. Their objective is to identify correlations, associations, clusters, patterns, and anomalies that summarize the underlying relationships in the database.

Data mining tasks and models Data mining tasks, or the tasks performed in the modelling phase of the KDD process, can be classified into predictive and descriptive tasks.

Other data-mining tasks include regression, summarization, dependency modeling and change, and deviation detection. Clustering and pattern recognition are forms of classification problems that differ on an important characteristic.

May 1, 2011 · Data mining algorithms can be implemented by custom-developed computer programs in almost any computer language. This obviously is a time-consuming task. In order for us to focus our time on data and algorithms, we can leverage data mining tools or statistical programing tools, like R, RapidMiner, SAS Enterprise Miner, IBM SPSS, etc., which can implement these algorithms with ease. These data ...